Idiap has a new opening for an Internship position in Spiking Networks for Prosody Synthesis

Idiap has a new opening for an Internship position in Spiking Networks for Prosody SynthesisMany audio events, such as those that happen in the vocal tract when speaking, can be characterised as having a start time and duration. The duration can be several samples or frames. However, this is at odds with current audio synthesis methods, which tend to use fixed-duration frame-based models. It follows that more natural audio synthesis may arise from more natural models.https://www.idiap.ch/en/allnews/spiking-networks-for-prosody-synthesishttps://www.idiap.ch/en/allnews/spiking-networks-for-prosody-synthesis/@@download/image/idiap-job-offer.jpg

Idiap has a new opening for an Internship position in Spiking Networks for Prosody Synthesis

Many audio events, such as those that happen in the vocal tract when speaking, can be characterised as having a start time and duration. The duration can be several samples or frames. However, this is at odds with current audio synthesis methods, which tend to use fixed-duration frame-based models. It follows that more natural audio synthesis may arise from more natural models.

At Idiap, we have developed a model of intonation in terms of fixed duration muscle responses. The model can explain an intonation contour well, but generation of new contours remains a research issue. The successful candidate will investigate how to generate such contours by means of spiking neural networks. Spiking networks are biologically plausible models that fit well with muscle response models.

The work is likely to involve a study of training methods for spiking networks from the literature. General familiarisation experiments should evolve into application focused ones when candidate methods are identified. Implementation may be custom, or may be based on software such as NEURON or BRIAN.

The internship would suit a masters graduate considering future PhD work, or a PhD candidate looking to diversify. Candidates should have a strong background in engineering, mathematics or a related discipline, should be computer-literate, and familiar with modern distributed programming environments and languages such as C++ and Python. Familiarity with deep learning tool-kits such as Torch or the ones above will be a distinct advantage.

The internship is offered for a period of six months beginning as soon as possible in 2018. Interns receive a stipend of CHF 2000 per month to cover accommodation and living costs.